Course Syllabus
Syllabus Statistics
Welcome
Welcome to Statistics! We’re so glad you’re here.
Every lesson is designed to help you grow as a thinker, problem solver, and global learner. As a Mizzou Academy global student, you will complete lessons and assignments on your own schedule, interacting with course content, participating in interactives, and completing practice activities, as well as drafting and revising assignments, preparing for quizzes and assessments, and taking exams.
To stay on track, we recommend using a pacing guide. You can find more information about pacing in the Course Resources section, along with helpful tools, technology support, and tips for online learning success.
As you begin, remember that online learning requires both independence and communication. Be curious, stay organized, and don’t hesitate to reach out to your teacher if you need support.
We’re excited to learn with you, and we’re happy you’re part of our Mizzou Academy community!
Pacing
This course can be completed in as few as six weeks or take up to 6 months (180 calendar days). The six weeks are counted from the date of the first lesson submission and not the date of enrollment.
This course is asynchronous, meaning you can complete lessons and assignments at your own pace.
Most students spend approximately 10 hours per lesson interacting with course content, participating in interactive activities, and completing practice exercises, as well as drafting and revising assignments, preparing for quizzes and assessments, and taking exams. Your time may vary depending on your goals and learning style.
We encourage you to work at a consistent pace, allowing time to absorb new ideas, build skills, and reflect on what you’ve learned. Use a pacing guide to plan ahead, stay organized, and finish strong.
Course Description
Statistics is about making appropriate conclusions from data, especially incomplete data.
You have encountered statistics in previous mathematics courses, in such things as calculating averages and drawing scatterplots of data. You continue to meet statistics in daily events such as weather forecasts, the news, and sports. People use statistics for a lot of things that affect you: allocating money to schools, deciding whether a medicine is safe and effective, keeping the right amount of food available, and setting prices.
Statistics can be misused. Suppose in the course of a week, you ate nothing for six days, and then you ate 21 meals on the last day of the week. It would be correct to claim you ate an average of three meals a day. But that would be misleading.
Critically interpreting claims about data is a skill of great value to you as a consumer of goods and services, as a citizen, and as a producer of goods and services. This course will help you ask the right questions about data, experiments, and surveys. This course will help you to draw the right conclusions.
This introductory course will provide you with a background in probability and statistics that you can use for basic data analysis and decision making. Lesson topics include summarizing and graphing data; statistics for describing, exploring, and comparing data; probability; probability distributions; normal probability distributions; estimates and sample sizes; and correlations and regressions.
Course Essential Questions
Essential Question
How can we use probability distributions and data summaries to estimate population characteristics and model the strength of relationships between variables?
Course Overview
Lesson |
Objectives |
Quiz |
Assignment |
|
1: Introduction to Statistics |
1.1: Classify a variable such as height or city by data categories such as qualitative data or interval level of measurement. 1.2: Recognize common flaws in data collection and analysis, such as small samples, convenience samples, misleading graphics, and confounding. 1.3: Apply desirable practices, such as simple random samples and experimental controls. |
13 multiple-choice questions |
No Assignment |
|
2: Summarizing and Graphing Data |
2.1: Make and read tables of frequency distributions or of relative frequency distributions. 2.2: Make and read histograms to display and interpret frequency distributions. 2.3: Graph data in other forms: Pareto chart, pie chart, dotplot, stem-and-leaf plot, scatterplot, time-series graph. 2.4: Describe the distribution a graph shows: uniform, normal, normal skewed left, normal skewed right, bimodal, clustered, has gaps, has outliers. Identify the center, variation, and patterns of change in the graphed distribution. |
12 multiple-choice questions |
No Assignment |
|
3: Statistics for Describing, Exploring, and Comparing Data |
3.1: Calculate mean, median, mode, and midrange (some measures of center). 3.2: Calculate range and standard deviation (two measures of variation). 3.3: Perform the above calculations for raw data and for frequency tables. 3.4: Calculate z scores, quartiles, and percentiles (some measures of relative standing). 3.5: Interpret these statistics, such as "his weight is 2.1 standard deviations above the mean." (Is that unusual?) 3.6: Construct boxplots to help understand center and variation. |
No Quiz |
Assignment: Lesson 3 Beginning data analysis |
|
4: Probability |
4.1: Calculate all the possible outcomes of a scenario. 4.2: Calculate how often either event A or event B will happen. 4.3: Calculate how often both event A and event B will happen. 4.4: Calculate how likely it is that event B will happen, under the condition that event A also happens. 4.5: Calculate how likely it is that an event will not happen. |
25 multiple-choice questions |
No Assignment |
|
5: Probability Distributions |
5.1: Identify a probability distribution associated with events such as rolling dice and compute the probability, mean, and standard deviation of data in a probability distribution. 5.2: Identify a binomial probability distribution, such as one that might occur in flipping a coin or in analyzing gender discrimination and compute the probability, mean, and standard deviation of data that satisfy the conditions of a binomial distribution. 5.3: Determine whether an outcome is unusual by its being outside the range μ + 2σ or by finding its theoretical probability. |
20 multiple-choice questions |
No Assignment |
Midterm Exam |
|||
|
6: Normal Probability Distributions |
6.1: Sketch the area of interest in a normal probability distribution. 6.2: Convert between z scores and raw values. Find probabilities given z scores and find z scores given probabilities. 6.3: Convert between nonstandard and standard normal distributions. 6.4: Distinguish between the population mean, a sample mean, and the mean of sample means. Similarly, distinguish between the population standard deviation, a sample standard deviation, and the standard deviation (standard error) of the sampling means. 6.5: Apply the central limit theorem to calculate sampling means and standard error. 6.6: When appropriate, approximate the binomial distribution with the normal distribution. 6.7: Judge whether a real distribution is adequately like the ideal normal distribution.
|
25 multiple-choice questions |
No Assignment |
|
7: Estimates and Sample Sizes |
7.1: Choose a binomial distribution, z distribution, or t distribution to calculate confidence. 7.2: Calculate how confident you are that a sample's estimate of proportion or mean is close to the actual population proportion or mean. This involves a confidence interval such as "plus or minus two years" and a confidence level such as "95%." 7.3: Determine how many observations you need to get specified amounts of confidence. |
20 multiple-choice questions |
No Assignment |
|
8: Correlations and Regression |
8.1: Find the correlation between two variables. 8.2: Determine whether a correlation is significant. 8.3: Find the linear regression equation between two variables. 8.4: When appropriate, use the linear regression equation to predict one variable given the other. 8.5: Distinguish between correlation and causation. |
No Quiz |
Assignment: Lesson 8 For this assignment, you will investigate two claims about household garbage, create two graphics, and prepare a report based on your findings. |
Final Exam |
|||
Grades
Your final grade will be based on the number of points you earn on submitted work and exams. The available points are distributed as follows:
| Source | Available Points |
|---|---|
| Lesson Assignments | 55 |
| Lesson Quizzes | 115 |
| Midterm Exam | 140 |
| Final Exam | 140 |
| Total | 450 |
Textbook & Technology Requirements
To fully participate, make sure you have:
- A computer that meets our Mizzou Academy technology requirements
- A microphone and webcam for recording audio and video assignments
- Any other required textbooks or materials for the course
Accessibility
If you anticipate barriers related to the format or requirements of this course, please let Mizzou Academy know as soon as possible. If disability-related accommodations are necessary (for example, a scribe, reader, extended time on exams, captioning), please contact Mizzou Academy.Canvas Technical Support
Canvas will be used as the primary platform for accessing course materials and assignments for this class.
- Access Canvas through the Tiger Portal https://mizzouacademy.missouri.edu/
- For assistance with Canvas, passwords, or other technical issues, submit a ticket by selecting Help from the Global Navigation menu on the left in Canvas. Additional information is provided in the following Canvas Guide: How do I get help with Canvas as a student?
- For questions about enrollment, access to courses, exam proctoring, or billing, contact our Support Services Team at (855) 256-4975 or mizzouacademy@missouri.edu.
Course Summary:
| Date | Details | Due |
|---|---|---|